83 citations · 174 across the 8 of their papers we have counts for
4 papers · 2 filters
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
The purpose of this study is to determine whether current video datasets have sufficient data for training very deep convolutional neural networks (CNNs) with spatio-temporal three…
Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
Convolutional neural networks with spatio-temporal 3D kernels (3D CNNs) have an ability to directly extract spatio-temporal features from videos for action recognition. Although th…
Collaborative Descriptors: Convolutional Maps for Preprocessing
Hirokatsu Kataoka, Kaori Abe, Akio Nakamura +1
The paper presents a novel concept for collaborative descriptors between deeply learned and hand-crafted features. To achieve this concept, we apply convolutional maps for pre-proc…
Changing Fashion Cultures
Kaori Abe, Teppei Suzuki, Shunya Ueta +3
The paper presents a novel concept that analyzes and visualizes worldwide fashion trends. Our goal is to reveal cutting-edge fashion trends without displaying an ordinary fashion s…